Development and Evaluation of a Digital Clinical Decision Support System for Caries Prevention

Thesis Abstract

Dental caries remains one of the most prevalent and persistent oral health challenges globally, particularly among vulnerable populations with limited access to preventive dental care. Despite advances in diagnostic technologies and preventive strategies, variability in clinical decision-making often impairs optimal caries management. This study aims to develop and evaluate a novel digital Clinical Decision Support System (CDSS) tailored to enhance caries prevention efforts among dental practitioners and patients. The primary objectives include designing the CDSS based on evidence-based protocols and behavioral theories, integrating it into existing clinical workflows, and assessing its impact on decision accuracy, preventive practices, and patient outcomes. Employing a mixed-methods research design, the study first involved the development phase using a user-centered design approach underpinned by the Health Belief Model and the Theory of Planned Behavior to inform system functionalities and user engagement strategies. The system was iteratively refined through focus group discussions with 15 practicing dentists and pilot testing with 50 patients across three dental clinics. The evaluation phase adopted a quasi-experimental, controlled pretest-posttest design involving 200 patients aged 6–15 years, randomly assigned to intervention and control groups. Data collection instruments included validated questionnaires assessing dentists’ decision-making confidence, preventive care provision, and patients' oral health behaviors, as well as clinical caries assessments conducted at baseline and three-month follow-up. Quantitative data were analyzed using descriptive statistics, paired t-tests, chi-square tests, and multiple regression analysis to ascertain the system’s impact on clinical decisions and patient outcomes. Thematic analysis was applied to qualitative feedback from practitioners and patients to explore system usability, acceptability, and perceived barriers. The anticipated results are that integration of the CDSS will significantly improve dentists’ adherence to evidence-based preventive protocols (p < 0.01), increase the delivery of personalized preventive advice, and reduce the incidence of new caries lesions over the follow-up period. Specifically, it is hypothesized that the intervention group will demonstrate a 25% reduction in caries incidence compared to controls, alongside higher scores in decision certainty and patient oral health behaviors. This research contributes novel insights into the design and implementation of digital decision support tools specifically for caries prevention, expanding the application of behavioral and cognitive theories in health informatics. It addresses existing gaps by providing empirical evidence on the effectiveness of an integrated, evidence-based decision aid in routine clinical practice, thereby bridging the gap between research and practice. Additionally, the study offers a conceptual framework for future development and dissemination of similar systems across diverse dental settings. The findings are expected to underscore the importance of integrating digital health tools in preventive dentistry to improve clinical accuracy, consistency, and patient-centered care. The study concludes that a well-designed CDSS can serve as a valuable adjunct to clinical judgment, promoting better preventive practices and reducing caries prevalence. Recommendations include further longitudinal studies to assess long-term outcomes, strategies for scaling system deployment across different healthcare environments, and ongoing training to enhance user acceptance and system utility. Overall, this research advocates for the strategic integration of digital decision support in dentistry as a means to advance preventive care outcomes and inform public health policies aimed at reducing the global burden of dental caries.